scholarly journals Optimal Dispatch of Aggregated HVAC Units for Demand Response: An Industry 4.0 Approach

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4320 ◽  
Author(s):  
Michael Short ◽  
Sergio Rodriguez ◽  
Richard Charlesworth ◽  
Tracey Crosbie ◽  
Nashwan Dawood
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Industry 4.0 ◽  
Energy Demand ◽  
Large Scale ◽  
Optimal Solution ◽  
Hvac Systems ◽  
Economic Incentives ◽  
Building Stock ◽  
The Real

Demand response (DR) involves economic incentives aimed at balancing energy demand during critical demand periods. In doing so DR offers the potential to assist with grid balancing, integrate renewable energy generation and improve energy network security. Buildings account for roughly 40% of global energy consumption. Therefore, the potential for DR using building stock offers a largely untapped resource. Heating, ventilation and air conditioning (HVAC) systems provide one of the largest possible sources for DR in buildings. However, coordinating the real-time aggregated response of multiple HVAC units across large numbers of buildings and stakeholders poses a challenging problem. Leveraging upon the concepts of Industry 4.0, this paper presents a large-scale decentralized discrete optimization framework to address this problem. Specifically, the paper first focuses upon the real-time dispatch problem for individual HVAC units in the presence of a tertiary DR program. The dispatch problem is formulated as a non-linear constrained predictive control problem, and an efficient dynamic programming (DP) algorithm with fixed memory and computation time overheads is developed for its efficient solution in real-time on individual HVAC units. Subsequently, in order to coordinate dispatch among multiple HVAC units in parallel by a DR aggregator, a flexible and efficient allocation/reallocation DP algorithm is developed to extract the cost-optimal solution and generate dispatch instructions for individual units. Accurate baselining at individual unit and aggregated levels for post-settlement is considered as an integrated component of the presented algorithms. A number of calibrated simulation studies and practical experimental tests are described to verify and illustrate the performance of the proposed schemes. The results illustrate that the distributed optimization algorithm enables a scalable, flexible solution helping to deliver the provision of aggregated tertiary DR for HVAC systems for both aggregators and individual customers. The paper concludes with a discussion of future work.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

Single Chip Microcomputer Cluster Management

2014 ◽  
Vol 933 ◽  
pp. 584-589
Author(s):  
Zhi Chun Zhang ◽  
Song Wei Li ◽  
Wei Ren Wang ◽  
Wei Zhang ◽  
Li Jun Qi
Keyword(s):  
Real Time ◽  
Management System ◽  
Large Scale ◽  
Fault Tolerant ◽  
Single Chip ◽  
Single Chip Microcomputer ◽  
Cluster Management ◽  
The Real ◽  
Time Performance ◽  
Operational Phase

This paper presents a system in which the cluster devices are controlled by single-chip microcomputers, with emphasis on the cluster management techniques of single-chip microcomputers. Each device in a cluster is controlled by a single-chip microcomputer collecting sample data sent to and driving the device by driving data received from the same cluster management computer through COMs. The cluster management system running on the cluster management computer carries out such control as initial SCM identification, run time slice management, communication resource utilization, fault tolerance and error corrections on single-chip microcomputers. Initial SCM identification is achieved by signal responses between the single-chip microcomputers and the cluster management computer. By using the port priority and the parallelization of serial communications, the systems real-time performance is maximized. The real-time performance can be adjusted and improved by increasing or decreasing COMs and the ports linked to each COM, and the real-time performance can also be raised by configuring more cluster management computers. Fault-tolerant control occurs in the initialization phase and the operational phase. In the initialization phase, the cluster management system incorporates unidentified single-chip microcomputers into the system based on the history information recorded on external storage media. In the operational phase, if an operation error of reading and writing on a single-chip microcomputer reaches a predetermined threshold, the single-chip microcomputer is regarded as serious fault or not existing. The cluster management system maintains accuracy maintenance database on external storage medium to solve nonlinear control of specific devices and accuracy maintenance due to wear. The cluster management system uses object-oriented method to design a unified driving framework in order to enable the implementation of the cluster management system simplified, standardized and easy to transplant. The system has been applied in a large-scale simulation system of 230 single-chip microcomputers, which proves that the system is reliable, real-time and easy to maintain.

scholarly journals Real-Time Safety Evaluation for Slope during Construction Using Numerical Forecast and Sensor Monitoring Platform

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2978 ◽  
Author(s):  
Sherong Zhang ◽  
Dejun Hou ◽  
Chao Wang ◽  
Xuexing Cao ◽  
Fenghua Zhang ◽  
...  
Keyword(s):  
Numerical Model ◽  
Real Time ◽  
Evaluation System ◽  
Large Scale ◽  
Safety Evaluation ◽  
The Real ◽  
Study Results ◽  
Data Feedback ◽  
Numerical Forecast ◽  
Slope Safety

Geology uncertainties and real-time construction modification induce an increase of construction risk for large-scale slope in hydraulic engineering. However, the real-time evaluation of slope safety during construction is still an unsettled issue for mapping large-scale slope hazards. In this study, the real-time safety evaluation method is proposed coupling a construction progress with numerical analysis of slope safety. New revealed geological information, excavation progress adjustment, and the support structures modification are updating into the slope safety information model-by-model restructuring. A dynamic connection mapping method between the slope restructuring model and the computable numerical model is illustrated. The numerical model can be generated rapidly and automatically in database. A real-time slope safety evaluation system is developed and its establishing method, prominent features, and application results are briefly introduced in this paper. In our system, the interpretation of potential slope risk is conducted coupling dynamic numerical forecast and monitoring data feedback. The real case study results in a comprehensive real-time safety evaluation application for large slope that illustrates the change of environmental factor and construction state over time.

Smoothly Rendering of Large-Scale Vector Data on Virtual Globe

2014 ◽  
Vol 631-632 ◽  
pp. 516-520
Author(s):  
Chao Yang ◽  
Shui Yan Dai ◽  
Ling Da Wu ◽  
Rong Huan Yu
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Smooth Transition ◽  
Vector Data ◽  
The Real ◽  
Virtual Globe ◽  
Multi Level

The method of view-dependent smoothly rendering of large-scale vector data based on the vector texture on virtual globe is presented. The vector texture is rasterized from the vector data based on view-dependent quadtree LOD. And the vector texture is projected on the top of the terrain. The smooth transition of multi-level texture is realized by adjusting the transparency of texture dynamically based on view range in two processes to avoid texture “popping”. In “IN” process, the texture’s alpha value increases when the view range goes up while In “OUT” process, the texture’s alpha value decreases. the vector texture buffer updating method is used to accelerate the texture fetching based on the least-recently-used algorithm. In the end, the real-time large-scale vector data rendering is implemented on virtual globe. The result shows that this method can real-time render large-scale vector data smoothly.

scholarly journals A Real-Time Deformation Monitoring Method for Large-Scale Structure Based on Relay Camera

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chuan He ◽  
Lianxiong Liu ◽  
Changhua Hu
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Large Scale Structure ◽  
Deformation Monitoring ◽  
Scale Structure ◽  
Monitoring Method ◽  
The Real ◽  
Intrinsic Parameters ◽  
Time Deformation ◽  
Extrinsic Parameters

In the process of the deformation monitoring for large-scale structure, the mobile vision method is often used. However, most of the existent researches rarely consider the real-time property and the variation of the intrinsic parameters. This paper proposes a real-time deformation monitoring method for the large-scale structure based on a relay camera. First, we achieve the real-time pose-position relationship by using the relay camera and the coded mark points whose coordinates are known. The real-time extrinsic parameters of the measuring camera are then solved according to the constraint relationship between the relay camera and the measuring camera. Second, the real-time intrinsic parameters of the measuring camera are calculated based on the real-time constraint relationship among the extrinsic parameters, the intrinsic parameters, and the fundamental matrix. Finally, the coordinates of the noncoded measured mark points, which are affixed to the surface of the structure, are achieved. Experimental results show that the accuracy of the proposed method is higher than 1.8 mm. Besides, the proposed method also possesses the real-time and automation property.

scholarly journals The research of the real-time pricing model based on the cumulated points system in the demand response

2018 ◽  
Vol 145 ◽  
pp. 246-251
Author(s):  
Peipei Zhang ◽  
Xueyin Wang ◽  
Mei Sun ◽  
Mingzhuang Zhang ◽  
Xu Yan
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Pricing Model ◽  
The Real ◽  
Model Based ◽  
Real Time Pricing

scholarly journals Strategy-making for a proactive distribution company in the real-time market with demand response

2016 ◽  
Vol 181 ◽  
pp. 540-548 ◽  
Author(s):  
Chunyu Zhang ◽  
Qi Wang ◽  
Jianhui Wang ◽  
Magnus Korpås ◽  
Mohammad E. Khodayar
Keyword(s):  
Real Time ◽  
Demand Response ◽  
The Real ◽  
Distribution Company ◽  
Strategy Making

Ground-Based Videometric Method and System for the Real-Time Measurement of Aircraft Landing Track

2014 ◽  
Vol 635-637 ◽  
pp. 824-831 ◽  
Author(s):  
Xiang Zhou ◽  
Zhi Hui Lei ◽  
Dan Fu ◽  
Xiao Hu Zhang
Keyword(s):  
Real Time ◽  
Global Positioning System ◽  
Large Scale ◽  
Time Measurement ◽  
Landing Point ◽  
The Real ◽  
Aircraft Landing ◽  
Real Time Measurement ◽  
Global Positioning ◽  
New Type

This paper proposes a ground-based videometric method and system for measuring the glide track of landing aircraft in real time. The proposed method is applicable for large-scale measurement via regional relays with multiple cameras. Its measurement ranges from kilometers away to the landing point, and it simultaneously fulfills the real-time measurement of the position and trajectory of aircraft. The real-time measurement result of the actual aircraft landing process shows a deviation from DGPS(Difference Global Positioning System) as small as 20 cm in the measuring region of 1 km. The proposed measurement method for aircraft landing track based on videometrics can establish a new type of landing aid system removed from radar and GPS.

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